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Local structural quantile effects in a model with a nonseparable control variable

具有非可分控制变量模型中的局部结构分位数效应

I consider a semiparametric version of the nonseparable triangular model of Chesher [Chesher, A., 2003. Identification in nonseparable models. Econometrica 71, 1405-1441]. The proposed model is linear in coefficients, where the coefficients are unknown functions of unobserved latent variables. Using a control variable idea and quantile regression methods, I propose a simple two-step estimator for the coefficients evaluated at particular values of the latent variables. Under…

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Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects

This paper empirically assesses the wage effects of the Job Corps program, one of the largest federally funded job training programs in the U.S. Even with the aid of a randomized experiment, the impact of a training program on wages is difficult to study because of sample selection, a pervasive problem in applied microeconometric research. Wage rates are only observed for those who are employed, and employment status itself may be affected by the training program. This paper…

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答复

Journal of Business and Economic Statistics. July 1, 2009, 27(3): 331-339. doi:10.1198/jbes.2009.08350. \nIn our article, we explain that the coefficients of the NKPC\nare not identified when λ = 0. For analytical tractability, our\nidentification analysis was based on the pure forward-looking\nversion of the NKPC but the result also applies to the hybrid\nversion [γb = 0 in Equation (2) in the article]; see, for example, Mavroeidis (2006).

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Weak Instrument Robust Tests in GMM and the New Keynesian Phillips Curve

GMM 中的弱工具变量稳健检验与新凯恩斯菲利普斯曲线

We discuss weak instrument robust statistics in GMM for testing hypotheses on the full parameter vector or on subsets of the parameters. We use these test procedures to reexamine the evidence on the new Keynesian Phillips curve model. We find that U.S. postwar data are consistent with the view that inflation dynamics are predominantly forward-looking, but we cannot rule out the presence of considerable backward-looking dynamics. Moreover, the Phillips curve has become…

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评论

Comment on "Weak instrument robust tests in GMM and the new Keynesian Phillips curve", Frank Kleibergen, Sophocles Mavroeidis. Journal of Business and Economic Statistics. July 1, 2009, 27(3): 293-311. doi:10.1198/jbes.2009.08280.

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Bias From Censored Regressors

解释变量删失导致的估计偏差

We study the bias that arises from using censored regressors in estimation of linear models. We present results on bias in ordinary least aquares (OLS) regression estimators with exogenous censoring and in instrumental variable (IV) estimators when the censored regressor is endogenous. Bound censoring such as top-coding results in expansion bias, or effects that are too large. Independent censoring results in bias that varies with the estimation method—attenuation bias in…

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Hierarchically penalized Cox regression with grouped variables

具有分组变量的层级惩罚 Cox 回归

In many biological and other scientific applications, predictors are often naturally grouped. For example, in biological applications, assayed genes or proteins are grouped by biological roles or biological pathways. When studying the dependence of survival outcome on these grouped predictors, it is desirable to select variables at both the group level and the within-group level. In this article, we develop a new method to address the group variable selection problem in the…

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Exact and asymptotic tests for possibly non-regular hypotheses on stochastic volatility models

随机波动率模型中可能非正则假设的精确与渐近检验

We study the problem of testing hypotheses on the parameters of one- and two-factor stochastic volatility models (SV), allowing for the possible presence of non-regularities such as singular moment conditions and unidentified parameters, which can lead to non-standard asymptotic distributions. We focus on the development of simulation-based exact procedures-whose level can be controlled in finite samples-as well as on large-sample procedures which remain valid under…

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Intervention and Causality: Forecasting Traffic Flows Using a Dynamic Bayesian Network

干预与因果关系:利用动态贝叶斯网络预测交通流

Real-time traffic flow data across entire networks can be used in a traffic management system to monitor current traffic flows so that traffic can be directed and managed efficiently. Reliable short-term forecasting models of traffic flows are crucial for the success of any traffic management system. The model proposed in this article for forecasting traffic flows is a multivariate Bayesian dynamic model called the multiregression dynamic model (MDM). This model is an…

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Intrinsically Autoregressive Spatiotemporal Models With Application to Aggregated Birth Outcomes

内禀自回归时空模型及其在汇总出生结局中的应用

A class of hierarchical Bayesian models is proposed for adverse birth outcomes such as preterm birth, which are assumed to follow a conditional binomial distribution. The log-odds of an adverse outcome in a particular county, logit(pi), follow a linear model that includes observed covariates and normally-distributed random effects. Spatial dependence between neighboring regions is allowed for by including an intrinsically autoregressive (IAR) prior or an IAR convolution…

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Partial Correlation Estimation by Joint Sparse Regression Models

利用联合稀疏回归模型估计偏相关

In this paper, we propose a computationally efficient approach -space(Sparse PArtial Correlation Estimation)- for selecting non-zero partial correlations under the high-dimension-low-sample-size setting. This method assumes the overall sparsity of the partial correlation matrix and employs sparse regression techniques for model fitting. We illustrate the performance of space by extensive simulation studies. It is shown that space performs well in both non-zero partial…

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ADMISSIBLE INVARIANT SIMILAR TESTS FOR INSTRUMENTAL VARIABLES REGRESSION

工具变量回归中可容许的不变相似检验

This paper studies a model widely used in the weak instruments literature and establishes admissibility of the weighted average power likelihood ratio tests recently derived by Andrews, Moreira, and Stock (2004, NBER Technical Working Paper 199). The class of tests covered by this admissibility result contains the Anderson and Rubin (1949, Annals of Mathematical Statistics 20, 46–63) test. Thus, there is no conventional statistical sense in which the Anderson and Rubin…

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A SIMPLE EFFICIENT INSTRUMENTAL VARIABLE ESTIMATOR FOR PANEL AR( p ) MODELS WHEN BOTH N AND T ARE LARGE

横截面与时间维度均大时面板 AR(p) 模型的简便有效工具变量估计

In this paper, we show that for panel AR( p ) models, an instrumental variable (IV) estimator with instruments deviated from past means has the same asymptotic distribution as the infeasible optimal IV estimator when both N and T , the dimensions of the cross section and time series, are large. If we assume that the errors are normally distributed, the asymptotic variance of the proposed IV estimator is shown to attain the lower bound when both N and T are large. A…

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OPTIMAL INVARIANT INFERENCE WHEN THE NUMBER OF INSTRUMENTS IS LARGE

工具变量数量较大时的最优不变推断

This paper studies the asymptotic behavior of a Gaussian linear instrumental variables model in which the number of instruments diverges with the sample size. Asymptotic efficiency bounds are obtained for rotation invariant inference procedures and are shown to be attainable by procedures based on the limited information maximum likelihood estimator. The bounds are obtained by characterizing the limiting experiment associated with the model induced by the rotation invariance…

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VALIDITY OF SUBSAMPLING AND “PLUG-IN ASYMPTOTIC” INFERENCE FOR PARAMETERS DEFINED BY MOMENT INEQUALITIES

矩不等式参数的子抽样与代入式渐近推断有效性

This paper considers inference for parameters defined by moment inequalities and equalities. The parameters need not be identified. For a specified class of test statistics, this paper establishes the uniform asymptotic validity of subsampling, m out of n bootstrap, and “plug-in asymptotic” tests and confidence intervals for such parameters. Establishing uniform asymptotic validity is crucial in moment inequality problems because the pointwise asymptotic distributions of the…

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Feasible estimation of firm‐specific allocative inefficiency through Bayesian numerical methods

通过贝叶斯数值方法估计企业特定的配置无效率

Abstract Both the theoretical and empirical literature on the estimation of allocative and technical inefficiency has grown enormously. To minimize aggregation bias, ideally one should estimate firm and input‐specific parameters describing allocative inefficiency. However, identifying these parameters has often proven difficult. For a panel of Chilean hydroelectric power plants, we obtain a full set of such parameters using Gibbs sampling, which draws sequentially from…

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Non-Parametric Identification and Estimation of Truncated Regression Models

截断回归模型的非参数识别与估计

In this paper, we consider non-parametric identification and estimation of truncated regression models in both cross-sectional and panel data settings. For the cross-sectional case, Lewbel and Linton (2002) considered non-parametric identification and estimation through continuous variation under a log-concavity condition on the error distribution. We obtain non-parametric identification under weaker conditions. In particular, we obtain non-parametric identification through…

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On the statistical identification of DSGE models

DSGE 模型的统计识别

Dynamic Stochastic General Equilibrium (DSGE) models are now considered attractive by the profession not only from the theoretical perspective but also from an empirical standpoint. As a consequence of this development, methods for diagnosing the fit of these models are being proposed and implemented. In this article we illustrate how the concept of statistical identification, that was introduced and used by Spanos [Spanos, Aris, 1990. The simultaneous-equations model…

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Identification of peer effects through social networks

通过社会网络识别同伴效应

We provide new results regarding the identification of peer effects. We consider an extended version of the linear-in-means model where interactions are structured through a social network. We assume that correlated unobservables are either absent, or treated as network fixed effects. We provide easy-to-check necessary and sufficient conditions for identification. We show that endogenous and exogenous effects are generally identified under network interaction, although…

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Following Germany's Lead: Using International Monetary Linkages to Estimate the Effect of Monetary Policy on the Economy

追随德国:利用国际货币联系估计货币政策的经济效应

Forward-looking behavior on the part of the monetary authority makes it difficult to estimate the effect of monetary policy interventions on output. We present instrumental variables estimates of the impact of interest rates on quarterly real output for several European countries, using German interest rates as the instrument. These estimates confirm a strong forward-looking bias in least squares estimates that persists even conditional on standard controls for the history…

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Improved JIVE Estimators for Overidentified Linear Models with and without Heteroskedasticity

同方差与异方差过度识别线性模型的改进 JIVE 估计量

We introduce two simple new variants of the jackknife instrumental variables (JIVE) estimator for overidentified linear models and show that they are superior to the existing JIVE estimator, significantly improving on its small-sample-bias properties. We also compare our new estimators to existing Nagar (1959) type estimators. We show that, in models with heteroskedasticity, our estimators have superior properties to both the Nagar estimator and the related B2SLS estimator…

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Likelihood ratio tests and singularities

似然比检验与奇异点

Many statistical hypotheses can be formulated in terms of polynomial equalities and inequalities in the unknown parameters and thus correspond to semi-algebraic subsets of the parameter space. We consider large sample asymptotics for the likelihood ratio test of such hypotheses in models that satisfy standard probabilistic regularity conditions. We show that the assumptions of Chernoff’s theorem hold for semi-algebraic sets such that the asymptotics are determined by the…

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An RKHS formulation of the inverse regression dimension-reduction problem

逆回归降维问题的再生核希尔伯特空间表述

Suppose that Y is a scalar and X is a second-order stochastic process, where Y and X are conditionally independent given the random variables ξ1, …, ξp which belong to the closed span LX2 of X. This paper investigates a unified framework for the inverse regression dimension-reduction problem. It is found that the identification of LX2 with the reproducing kernel Hilbert space of X provides a platform for a seamless extension from the finite- to infinite-dimensional settings.…

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Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality

用局部工具变量估计潜在结果分布:大学入学与工资不平等应用

This paper extends the method of local instrumental variables developed by Heckman and Vytlacil [Heckman, J., Vytlacil E., 2005. Structural equations, treatment, effects and econometric policy evaluation. Econometrica 73(3), 669-738] to the estimation of not only means, but also distributions of potential outcomes. The newly developed method is illustrated by applying it to changes in college enrollment and wage inequality using data from the National Longitudinal Survey of…

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